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AI in logistics: handing exceptions to the next shift

Short answer

AI in logistics helps you prepare the handover of open cases to the next shift. Events from the system, messages and the operator's notes go into a short description: what is confirmed, what we are waiting for and who takes the next step. Start with one kind of exception, for example deliveries waiting for a confirmed time.

How we workDetails ↓

  1. 01Call30 minutes with an engineer, free
  2. 02PrototypeA working system on your process and data, free
  3. 03ImplementationTarget and fixed price in the contract; 50% at signing
  4. 04Acceptance50% once the agreed target is met
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Author: Syntalith · 4 min read

Example: the morning request inbox
Agent · ready

Statistics

Logistics and AI: statistics 2026

1.6 mo.

payback of €3,000 at 900 exceptions a month: €2,618 of work today, €793 with checking and the model. Scenario.

Figures checked: 22 October 2026

Handing an exception to the next shift
  1. 01Identifierthe shipment and the time of the event
  2. 02Confirmedwhat the system events show
  3. 03Waitingfor what, and from whom
  4. 04Next stepwho, and by when

First the identifier and the time of the event

Link the materials to a specific order or shipment. A similar client name is not enough, especially when you handle several deliveries on the same day. Also record when the event happened and when the information reached the system. A message received later can describe an earlier state.

GS1 describes EPCIS as a standard for sharing event data, covering among other things the object, the time, the place and the business context of a movement in the supply chain. It is an example of ordering information that a later summary can use. It does not mean that your TMS or WMS already supplies such data, or that a simple summary needs the whole standard rolled out. GS1 description, checked on 9 October 2026.

A planned time does not confirm a delivery

In a fictional exercise, the system shows a planned receipt at 14:00. At 13:40 the operator gets a message that the carrier expects to arrive at 16:00. At 14:15 there is still no event confirming receipt. From this data you can write a description of the delivery still awaited and give the new forecast. You cannot state that the delivery arrived at 14:00.

In the handover, record separately the time from the plan, the carrier's forecast and the lack of confirmation that it happened. Add the source of the message and who is to check what happens next. If a time for the next contact was agreed, keep it as the next task; do not add one on the strength of the model's guess.

In the next version of the exercise, add a late receipt message. Check whether the summary uses the time of the event itself, whatever order the messages arrived in. None of these versions describes a completed rollout.

What should the person taking over the case see?

InformationWhy it is needed
Case number and sourceTo open the right order
The last confirmed stateTo tell what happened from what was planned
The open questionTo know which answer we are waiting for
The owner and the agreed next stepSo that the case is not left unhandled

Before the list goes out, the operator should check how messages were assigned and how exceptions were described. If a standard TMS report already gives such a view, use it as the reference point. AI makes more sense for free-text notes and correspondence that someone has to read and shorten.

If delays also arise outside the shift handover, look at choosing automation in logistics. Missing data, a WMS rule and the physical movement of goods each need their own assessment.

If open cases arrive mainly by email, review the proposed scope for transport email. It covers several requests in one thread and a reply that closes only one of them. That helps you decide what should stay on the list for the next shift.

How do you assess the first scope?

Compare the prepared summary with a manual handover of the same cases. Record missed exceptions, wrong assignments and sentences that suggest something happened when it was not confirmed. Measure the time it takes to check the whole list. A shorter description does not help if the next shift has to read every message again.

You can first practise preparing the note in the company's own tool. Syntalith's offer for transport and logistics lets you compare training with process automation; the basis for pricing is on the pricing page. Pulling events automatically and writing to the TMS require the available connections to be confirmed and responsibility for exceptions to be settled.

If the problem is questions about the current packing rules, that is a different scope: a knowledge base for contract logistics. A shift handover is about the current state of a specific case. Start that conversation with information the previous shift did not manage to hand over and the next one had to reconstruct.

What it costs

Scenario: 900 exceptions a month
Today
900 exceptions × 5 min = 75 h (€2,618)
With the system, a person checks the result in 30% of the time
€785
Model, 1 call per case, Claude Sonnet 5.5
€7
Cost of one case
€2.91 today, €0.88 with the system
Saving
€1,825 a month

Payback of €3,000

1.6 months

The volume, the time and the checking share are the scenario's assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Model: 3,000 input tokens and 300 output tokens per call at Anthropic's rates, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

What we measure in the trial
  • The time from receiving a case to the result, before and after the change
  • Cases the application passed to a person
  • Corrections by the person checking
  • The cost of the model and maintenance at the target volume

Where to start

In the free review we choose one process and count the volume and the team's working time, and within 2 working days you receive a written summary with a price. We build the automation as part of AI automations, from €3,000 net.

Worked example · Scenario

How we count the payback: a shift handover

We run the same count for your warehouse in the free review.

€1,745

a month for retyping 1,000 CMR and POD documents

Payback: 2 mo.

3 minutes per document and checking in 15% of the old time are our assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat, for companies with 10 or more employees. We use it here in place of a transport sector wage. Model cost: 0.007617 USD per reading, measured in our system, which is about €0.0069 per document, at the ECB rate of 1.1205 USD per euro on 22 October 2026.

See the full calculation →

This is how we implement it in companies

All case studies →

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗

Start with the process that takes the most time each week.Book a free process review (30 min) →

How we build automation and agents

From a conversation to a working system in four steps.

  1. 01 · 30 min

    Free process review

    €0

    You're talking to an engineer. You receive the written plan within 2 business days.

  2. 02 · 5 days

    Free prototype

    €0

    The system works on 20-100 cases that your team has already handled. You see every result.

  3. 03 · 2–16 weeks

    Build

    50%

    Fixed price and goal written in the contract. First installment upon signing.

  4. 04 · after reaching the goal

    Reception

    50%

    You pay the second installment when the system reaches its target on your cases.

How a free prototype is created

Mon.

We set a goal

What result do you consider good?

Tue–Wed

The system is working

It goes through your affairs, one by one.

Thu

We compare

We check every difference with the team's work.

Fri

Result and price

List of errors and fixed implementation price.

You choose the matters. We anonymize them upon request, they stay in the EU and we delete them after the test.

On the market, such a test usually costs from PLN 3,000 to PLN 8,000.

Book a free process review (30 min)

We establish a prototype during a free analysis.

Data checked on October 21, 2026.

„Is my data safe?”

Yes. You choose where they go: from your company account to the model on your server.

  1. 00Employee's private account

    Customer and company data ends up in an account that the company cannot see or control. There is no data processing agreement, so it is a violation of the GDPR. When an employee leaves, the chat history goes with them.

  2. 01ChatGPT or Claude corporate account

    The provider does not use your data to train models. A copy of the queries remains in his logs for up to 30 days.

  3. 02API with zero retention (ZDR)

    The provider processes the request and does not save anything. It requires his consent, we prepare the application together.

  4. 03Processing in the EU

    Queries are counted and stored in Europe: OpenAI in the EU region, Claude via clouds with the EU region.

  5. 04Model at your place

    The open model runs on your server or in your cloud in the EU. The data does not go outside the company.

What we do with every implementation

  • Confidentiality agreement and data processing agreement before we receive any data.
  • You choose the cases for the prototype and we anonymize them upon request.
  • The data stays in the EU and we delete it after the test.
  • Corporate accounts with an administrator on your side.

When data cannot leave the company

The open model runs on your server or in your cloud in the EU. To choose from:

White-tailed eagle
Polish model, SpeakLeash and ACK Cyfronet AGH
PLLUM
Polish model, HIVE consortium commissioned by the Ministry of Digitization
Qwen
Alibaba
GLM
Zhipu AI
DeepSeek
DeepSeek

We select a model for the task and check it on your cases. We run it, tune it and maintain it.

Source: Bielik and PLLuM, ACK Cyfronet AGH ↗ · PLLuM, Ministry of Digitization ↗

Do you have a lot of your own data? We will fine-tune the small model.

  1. 1 Your examples
  2. 2 tuning
  3. 3 test on new cases
  4. 4 model at your place

When you have thousands of similar emails, documents or reports, we teach a small open model based on your examples. It works for you, responds quickly and costs less to maintain than a large model. We measure quality on issues that the model has not seen while learning.

Przemysław and Piotr did it in large programming and consulting companies. Artem did it before and does it today at Syntalith. It's about models on your own infrastructure, tuning and quality measurement.

You choose the protection level during the interview. We sign the data processing agreement before we see any data.Schedule a free analysis →

AI implementation

Start with the process that takes the most time each week.

The engineer chooses one process with you and calculates how much it costs today. Then we build a free prototype on 20-100 cases that your team has already handled. We write down the goal and the fixed price in the contract.

See AI implementation →
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

Questions

  • How does AI help with a shift handover in logistics?

    It gathers events, messages and notes on open cases into a description: what is confirmed, what we are waiting for and who takes the next step, with the identifier and the time of the event.

  • Does a planned time confirm a delivery?

    No. The handover keeps the planned time apart from the confirming event, for example receipt at the warehouse.

  • How much does it cost?

    At Syntalith, AI apps, automations and agents start from €3,000 net. At 900 exceptions a month and 5 minutes each, the payback is 1.6 months.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
You buy accounts directly from OpenAI or Anthropic and receive an invoice from them. We do not add anything to the license.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.